The Impact of Gender and Personality Traits on Inhibitory Control in Adolescents

Research Study 1

The first study is about investigating the impact of gender, level of agreeableness, conscientiousness, extroversion, openness to experience, and neuroticism on the inhibitory control in adolescents. That is, we are trying to find out whether there is the statistically significant impact of gender, level of agreeableness, conscientiousness, extroversion, openness to experience, and neuroticism on the inhibitory control in adolescents. Thus, for this purpose, we shall be performed multiple regression analysis with gender, level of agreeableness, conscientiousness, extroversion, openness to experience, and neuroticism as independent variables and the inhibitory control in adolescents as the dependent variable. For those seeking support, psychology dissertation help can be invaluable in navigating this complex analysis. So, the main research question that we shall be answering through this analysis is “How do stimuli such as gender, level of agreeableness, conscientiousness, extroversion, openness to experience, and neuroticism affect the inhibitory control in adolescents?” That is, whether these stimuli suppress or aid adolescent behaviour reactions.

Regression Analysis

Descriptive Analysis

The table below shows the descriptive statistics for each of the independent variables and the dependent variable which were measured on a continuous scale:

As per the above table, the personality trait which has got the highest mean score is Agreeableness followed by Conscientiousness, Openness, Neuroticism and Extroversion.

Correlation

The table below shows the correlation between the dependent and the independent variables:

As per the correlation table, there is positive association between Inhibitory Control and the independent variables, except Extroversion and Neuroticism. Further, as the p-value or the significance value is coming out to be 0.000, which is less than the critical alpha value of 0.05, except for Neuroticism, it can be said that apart from Neuroticism, the dependent variable is statistically significantly associated with all the other independent variables. Positive association means, greater the personality traits, higher the level of control and vice versa. On the other hand, negative association means, greater the personality traits, lower the level of control and vice versa.

Model Summary

The model summary shows the level of impact the independent variables on the dependent variable.

As per the above table, the regression analysis R2 comes out to be 0.886. This shows that the independent variables predict the variation of 88.6 percent in the dependent variable. However, whether this prediction is statistically significant or not can be seen from the ANOVA analysis

ANOVA Analysis

As per the ANOVA analysis F(6, 268) = 346.942; p = 0.000. Since the p-value or the significance value is coming out to be 0.000, which is less than the critical alpha value of 0.05, it can be said that the above relationship is statistically significant. That is, independent variables gender, level of agreeableness, conscientiousness, extroversion, openness to experience, and neuroticism have a statistically significant impact on the dependent variable inhibitory control in adolescents.

Coefficient Table

As per the coefficient table, the p-value or the significance value for agreeableness, conscientiousness, extroversion and openness is coming out to be 0.000, which is less than the critical alpha value of 0.05, it can be said that agreeableness, conscientiousness, extroversion and openness have statistically significant impact on inhibitory control in adolescents, whereas, sex and neuroticism do not have statistically significant impact on inhibitory control in adolescents. Thus, the final regression equation comes out to be as follows:

Inhibitory Control=22.426+0.468*Sex+0.417*agreeableness+ 0.247*conscientiousness- 0.653*extroversion+ 0.371*openness- 0.026*neuroticism

Thus, from the regression analysis, it can be said that personality trait has a statistically significant impact on the behaviour reactions of an adolescent. Further, as the majority of the independent variables which have a statistically significant impact on the dependent variable are positively associated with an independent variable, it can be assumed that higher personality trait scores aid to adolescent behaviour reactions.

Research Study 2

The second study determines whether self-reported proficiency in a video game has a statistically significant impact on the size of adolescents’ amygdale brain structure. That is, the study tries to find out whether there is a difference in amygdala brain structure of an adolescent between novice, moderate and expert. Alternatively, which group of video game proficiency has the largest structure. To perform this study, ANOVA was performed to make a comparison of amygdale brain structure of an adolescent between three groups, that is, novice, moderate and expert. Therefore, the research question which this study tries to answer is “Does there exist different in Amygdala Volume (cubic cms) between self-reported proficiency in video game groups?” The table below shows the descriptive statistics of Amygdala Volume (cubic cms) for the three groups:

As per the above table, the Amygdala Volume (cubic cms) is highest in expert followed by moderate and novice groups. Further, the highest and the lowest Amygdala Volume (cubic cms) for novice, moderate and expert group is 9.11 cubic cms and 63.34 cubic cms; 7.96 cubic cms and 66.51 cubic cms; and 19.68 cubic cms and 71.50 cubic cms respectively. However, whether this difference in the Amygdala Volume (cubic cms) between the group is statistically different or not can be judged from the ANOVA analysis.

ANOVA Analysis

As per the ANOVA analysis F(2, 272) = 6.502; p = 0.002. Since the p-value or the significance value is coming out to be 0.002, which is less than the critical alpha value of 0.05, it can be said that the above difference between the three groups, that is, novice, moderate and expert, is statistically significant. That is, Amygdala Volume (cubic cms) statistically significantly varies between self-reported proficiency in video game group. Now, the ANOVA analysis has made this clear that there is a statistically significant difference in Amygdala Volume (cubic cms) between novice, moderate and expert. However, to exactly know where the difference exists, that is between all the three groups or any two groups, we need to analyse the multiple comparison table below:

As per the above table, the p-value or the significance value between novice and moderate is coming out to be 0.210, which is greater than the critical alpha value of 0.05. This means there is no statistically significant difference in Amygdala Volume (cubic cms) between novice and moderate. Further, the p-value or the significance value between novice and expert is coming out to be 0.001, which is less than the critical alpha value of 0.05. This means there is a statistically significant difference in Amygdala Volume (cubic cms) between novice and expert. Finally, the p-value or the significance value between moderate and expert is coming out to be 0.011, which is less than the critical alpha value of 0.05. This means there is a statistically significant difference in Amygdala Volume (cubic cms) between moderate and expert. Thus, from the overall analysis, it can be said that there is a statistically significant difference in Amygdala Volume (cubic cms) between novice and expert; and moderate and expert. That is, Amygdala Volume (cubic cms) between novice and moderate is not statistically significantly different. Therefore, from the overall analysis, it can be said that video game players whom self-reported proficiency in video games, that is, who are expert, have a higher concentration of Amygdala Volume (cubic cms) as compared to moderate and novice video game players. The graph below also shows that the mean of Amygdale Volume (cubic cms) is highest for expert followed by moderate and novice.

Research Study 3

The research study 3 is about investigating possible differences in reaction times before and after sleep training. The aim of the study was to determine whether sleeping training has a statistical impact on the reaction time on a video game. That is, whether sleeping training improves or deteriorates reaction time on a video game. For this purpose, a paired sample t-test was performed. In this, first reaction time before the test was recorded and then sleeping training was provided to the participants. After imparting sleeping training, again reaction time was measured, to determine whether the reaction time has improved or deteriorated. So, in this study, the main research question is “Does imparting sleeping training significantly improves the reaction time?” The results of the paired t-test are as follows:

Paired Sample Statistics

As per the above table, the mean of reaction time post-test is higher as compared to mean of reaction time pre-test. This shows that post-test, there is slower reaction time. That is, the reaction time has increased after imparting sleeping training to the participants. However, to determine whether this difference in reaction times before and after training is statistically significant or not, we need to analyse the t-test table below:

Paired Sample t-test

As per the above table, the mean difference between pre-test reaction time and post-test reaction time is coming out to be negative 26.320. This clearly shows that the reaction time has increased after imparting training to the participants. Further, t(274) = -2.009; p = 0.045. As the p-value or the significance value is coming out to be 0.045, which is less than the critical alpha value of 0.05, it can be said that there is a statistically significant difference between the pre-test reaction time and post-test reaction time. That is, the post-test reaction time is statistically significantly higher than then pre-test reaction time. Thus, from the overall analysis, it can be said that sleeping training results in significant increase in the reaction time, or in other words it can be assumed that sleeping training slower the reaction time.

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